This document showcases someLANDFIRE-powered maps and charts for the
Green Mountain National Forest in Vermont. In general LANDFIRE enables
an assessment of past and present ecosystems and their disturbances plus
the ability to make comparisons. LANDFIRE does not address climate
change, or set “Desired Future Conditions”. 1 exploring potential impacts of climate change and how
management actions may or may not lead to desired future conditions may
be accomplished using SyncroSim and
TNC’s
modeling site for more information.
Due to the name and major funding sources LANDFIRE is often thought
of as a fire dataset. While LANDFIRE does deliver many fire-focused
datasets (e.g., the 40 Scott and Bergan Fire Behavior Fuel Models. Visit
here) for more
information], this assessment is focused on the vegetation datasets.
Additionally-this document is meant to be a conversation starter, and
does not include the many possibilities brought to the table by NIACS
for example.
A few characterisitics of LANDFIRE data and this report
LANDFIRE products are designed for use on large areas, typically
comparing watersheds to watersheds for example. Often users ask “how
small of an area can we use LANDFIRE data?” which is a tough question to
answer as it varies based on data quality, heterogeneity of the
vegetation (and underlying driving factors such as soils), and the
particular dataset(s) being considered. Further, the purpose of data use
is of particular importance. Using the data to explore trends is one
thing, using LANDFIRE (or any data for that matter) to make
place-specific decisions is another.
Schematic illustrating need for more
review of data for smaller landscapes.
LANDFIRE data has been successfully used for mid-scale planning (~10k
acres), but that was after considerable review by experts. To use data
for smaller areas or for more detailed decision making requires more
review per unit area (see graphic in sidebar).
LANDFIRE spatial data is delivered in raster format with 30m pixel
size. Attribute tables can range from fairly simple (e.g., Existing
Vegetation Cover), to rich with many fields (e.g., the Biophysical
Settings data which includes historical fire regime information).
This report was created using free data and software. Data was
downloaded from https://landfire.gov/getdata.php, all GIS processing and
charts created in R2R, and all maps created in Quantum GIS3QGIS.
The report itself was written as an R-Markdown4 Learn more about r-markdown documents here. document.
It is not necessary to use these tools! One could just as easily use
ESRI and Microsoft products.
Which ecosystems were dominant prior to European Colonization?
With climate change, invasive exotic species, resource extraction and
other modern ecosystem drivers it can be difficult to develop a
baseline, or understanding of what was on the landscape prior to
European colonization. LANDFIRE has a product suite under the
Biophysical Settings (BpS)5 LANDFIRE defines Biophysical Settings as “the vegetation
system that may have been dominant on the landscape prior to
Euro-American settlement and is based on both the current biophysical
environment and an approximation of the historical disturbance regime” label that includes three components. The
BpS Descriptions6 find yours at here and accompanying
state-and-transition models7 download from this site. These documents and
models describe how over 900 BpSs of the U.S. looked and worked
historically. Each one includes a description of the major succession
classes, and estimated amounts of each succession class based on natural
disturbance regimes. Learn more about these products and their
development by reading Blankenship
et al. (2021).
Also included are the BpS spatial data8 learn more here. This raster data
includes a robust attribute table with information on historical fire
regimes in addition to multiple classifications of the BpSs (e.g., there
are lumped schemes).
Green Mountain NF dominated by Northern Hardwood Forests
historically
Based on LANDFIRE BpS data three BpSs were present on over 90% of the
landscape as shown in the chart and map below. Both graphics are not
complete-there are more BpSs mapped than indicated on both. Lists were
shortened for clarity, and to remove possible noise. A complete list and
mapped amounts are available from the author.
Biophysical Settings Map, Proclamation Area with Ownership Boundary
in black
Also possible with the BpS products:
quantification of historical disturbance amounts per year, including
different types of fire and wind/weather/stress
mapping of historical fire regimes
delving into the state-and-transition models to explore and refine
historical fire regimes to better match local knowledge, develop current
condition models to document current disturbances and to modify to
capture potential changes to disturbance regimes with climate
change
In the last section of the document we will explore a couple ways to
compare this historical data to current data.
Historical fire on the Green Mountain NF
The LANDFIRE Biophysical Settings spatial data includes modeled
historical Mean Fire Return Intervals (MFRI) for surface, mixed,
replacement and all fires. By converting the MFRI to an annual
probability (1/MFRI) then multiplying the annual probability by the
acres of each BpS you can approximate the annual historical fire
amounts.
Within the Ownership Boundary there was roughly 500 acres of
fire per year prior to European Settlement
What does the existing vegetation look like?
LANDFIRE delivers multiple datasets9 visit the Vegetation page to get
more information used to characterize
current conditions. Below are charts and maps of Existing Vegetation
Type (EVT), Cover (EVC) and Height (EVH).
The EVT data represents conditions as of ca 2016. This dataset is
currently (January, 2022) to represent conditions as of ca2020. Release
data TBD.
Green Mountain NF dominated by Northern Hardwoods Forests as
of ca2016
Based on LANDFIRE EVT data there appears to be a loss of the swamp
systems. What is not clear from simply reviewing Bps and EVT data is an
assessment of what converted to what. Additionally, colors were not
matched between the BpS and EVT maps. Both graphics are not
complete-there are more EVTs mapped than indicated on both. Lists were
shortened for clarity, and to remove possible noise. A complete list and
mapped amounts are available from the author.
Green Mountain NF dominated by forests with relativity high
canopy cover as of ca2016
As expected most of the Green Mountain NF is mapped as the “forest”
lifeform. It appears that most of the landscape is in a closed canopy
condition.
Note: the data is delivered in 1% increments. In the graphics below
the cover was categorized into 10% bins for viewing. I am happy to share
raw attribute tables for further review.
Green Mountain NF dominated by forests with most pixels
mapped between 15-20M as of ca2016
As in the chart above most of the landscape is mapped as the “forest”
lifeform. LANDFIRE mapped most of the pixels as having an average height
between 15-30M with a range of 3-38M.
Note: the data is delivered in 1% increments. In the graphics below
the cover was categorized into bins (different for each lifeform) for
viewing. I am happy to share raw attribute tables for further
review.
Comparing historical and current vegetation
There are two main ways to compare historical with current vegetation
conditions using LANDFIRE data:
Directly comparing the BpS and EVT data
Assessing over/under representation of succession classes10 aka structural stages of each BpS. Learn more here
Below I present a couple ways to graphically represent these two
types of comparisons.
Comparing the BpS and EVT datasets
In the BpS and EVT charts above it is possible to visually compare
how amounts of different ecosystems have changed over time, but
you cannot assess how a particular type has changed at a pixel by pixel
level. To do so requires doing a “stack” or “combine” of the BpS and EVT
datasets so each pixel gets both a BpS label and an EVT label. Once you
have that in hand you can visualize the results in multiple ways. One
possibility is a sankey diagram such as the one included below. Here I
have greatly lumped vegetation types. It is possible to
create a more detailed sankey charts without the lumping. Even with the
lumping a few patterns emerge, for example a “conversion” of some of the
Coniferous to Hardwoods.
Comparing the succession classes within particular
BpSs
Each BpS has descriptions and mapping rules for up to 5 succession
classes. These succession classes are largely defined by canopy cover
and height, by some degree by composition. Using results from the models
we get a “Reference” or expected percentage of each s-class. Using
mapping we get the current percentages.
The following chart represents reference and current percentages of
succession classes for 3 selected BpSs (ones that were fairly dominant
historically).
Comparing LANDFIRE EVT and Vermont’s Significant Natural Communities
data**
The Vermont Agency of Natural Resources tracks the best examples of
natural community types that were downloaded on 7 March 2022 from the VT
Open Geodata Portal. These most likely represent the best dataset by
which to compare LANDFIRE EVT data.
To do so I did a “combine” in ArcGIS Pro (spatial analyst toolbox) of
the Significant Natural Communities (SNC) and EVT data. Due to data
scale use issues, I filtered out the rarest 5% of the SNCs then the
rarest 5% of the EVT data that was mapped to each SNC. Below is a Sankey
chart to visually compare the results, then the raw data table.
Schematic illustrating need for more
review of data for smaller landscapes.
